Ye Yuan

5.4k citations
65 papers · 3.4k indexed · 2 hit papers · h-index 25
Topics
Single-cell and spatial transcriptomics (8 papers)Gene expression and cancer classification (8 papers)Spine and Intervertebral Disc Pathology (6 papers)

In The Last Decade

Ye Yuan

59 papers receiving 3.3k citations

Hit Papers

Understanding Convolution for Semantic Segmentation2018202620202023201820194008001.2k

Peers

Ye Yuan
Comparison fields: 5 of 166
  • Computer Vision and Pattern Recognition 1.4k
  • Molecular Biology 924
  • Artificial Intelligence 422
  • Biomedical Engineering 329
  • Media Technology 310
Replace Zoltán Benyó with:
Zoltán Benyó Hungary
Yun Zhai China
Xiaofei He China
Luping Zhou Australia
Ming‐Tat Ko Taiwan
Yoshihiko Hamamoto Japan
Jing Qin China
Hyunsoo Kim South Korea
Douglas A. Gray Australia
Qiong Cao China
Ye Yuan relative to Zoltán Benyó Hungary Zoltán Benyó's profile →
Citations per field
00.5×3.3×
Zoltán Benyó · 1×
Citations per year

Countries citing papers authored by Ye Yuan

Since Specialization
Citations

This map shows the geographic impact of Ye Yuan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ye Yuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ye Yuan more than expected).

Fields of papers citing papers by Ye Yuan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ye Yuan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ye Yuan. The network helps show where Ye Yuan may publish in the future.

Co-authorship network of co-authors of Ye Yuan

This figure shows the co-authorship network connecting the top 25 collaborators of Ye Yuan. A scholar is included among the top collaborators of Ye Yuan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ye Yuan. Ye Yuan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 1
5 14
6 1
7 29
8 77
9 114
10 6
11 27
12 16
13 15
14 11
15 122
16
Understanding Convolution for Semantic Segmentationbreakdown →
1366
17 40
18 1
19 33
20 44

About Ye Yuan

Ye Yuan is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Cancer Research, having authored 65 papers that have together received 3.4k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (8 papers), Gene expression and cancer classification (8 papers) and Spine and Intervertebral Disc Pathology (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.4k citations), Media Technology (310 citations) and Biophysics (94 citations). Ye Yuan has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Garrison W. Cottrell, Pengfei Chen, Ding Liu, Xiaodi Hou, Panqu Wang, Zehua Huang, Ziv Bar‐Joseph, Wuyang Chen, Yang Yang and Zhou Ren. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Bioinformatics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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